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Tutorial

This page contains step-by-step instructions for the tutorial on artificial neural networks (NN) in TMVA. In order to follow it, you need an access to a computer with a recent version of ROOT installed (and the TMVA package as a part of it). Start by checking out the tutorial's repository as explained in the README.

Introduction

The TMVA package includes a number of MVA methods, with NNs among others, incorporated into a common framework. The manual can be found here; keep it opened during the session.

The tutorial addresses the task of binary classification, by an example of discrimination between tH, H->bb and semileptonic ttbar events. A number of observables have been chosen to distinguish between the two. ROOT tuples with the observables are available in the data/ directory of the repository. For each process several tuples are provided, varying in the number of events.

The tutorial is focused on the usage of TMVA rather than illustrating various aspects of NNs as a machine learning technique.